KAIS
2008
13 years 4 months ago
2008
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
ICASSP
2010
IEEE
13 years 4 months ago
2010
IEEE
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
SDM
2008
SIAM
13 years 5 months ago
2008
SIAM
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
GIS
2008
ACM
14 years 5 months ago
2008
ACM
In this paper, we discuss an application of spatial data mining to predict pedestrian flow in extensive road networks using a large biased sample. Existing out-of-the-box techniqu...